Modern methods in digital signal and speech processing have made it possible to control a target system by recognizing a spoken command and then applying a stimulus to the target system based on the recognized spoken command. Typically, when a spoken command is identified by a speech recognition system, the spoken command is one of a group of commands represented in a command database. Additionally, speech systems are well suited to control software applications having a menu type user interface. Target systems and software applications controlled using voice commands are desirable because a user can control the target systems or applications by speaking commands thereby improving the ease of operation and user friendliness perceived by the user.
A problem with existing speech recognition systems is that the systems require large amounts of processing and data storage to produce modest recognition success. Additionally, existing systems support small command databases and have difficulty adding new commands and retraining existing commands. Another problem with existing voice command systems is the expensive processing required to remove noise and channel effects from input spoken commands.
Thus, what is needed is, an improved independent speaker recognition system and method for training, retraining, and recognizing spoken commands. What is also needed is a system and method requiring less processing and storage requirements when supporting large command databases. What is further needed is a system and method of removing noise and channel effects in an inexpensive and efficient manner. Also needed are a system and method for more efficiently adding new commands and retraining and reinforcing existing commands.